AIJ Journal of Technology and Design
Online ISSN : 1881-8188
Print ISSN : 1341-9463
ISSN-L : 1341-9463
Information Systems Technology
STUDY ON DETOUR PATH DERIVATION FOR 7-AXIS ROBOT USING DEEP REINFORCEMENT LEARNING
Ryoji FUJIOKAYosuke NAKAOGakuhito HIRASAWA
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JOURNAL FREE ACCESS

2022 Volume 28 Issue 70 Pages 1602-1606

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Abstract

The 7-axis articulated robot can arbitrarily rotate the position of the elbow by changing the angle of the 7th axis. When a 7-axis articulated robot makes a detour, it is necessary to properly control both the position and orientation of the tool and the E-axis angle. In this study, we propose a deep reinforcement learning method for automatically generating detour paths including control of the 7th axis.

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© 2022, Architectural Institute of Japan
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